Cell-free massive MIMO is emerging as a promising technology for future wireless communication systems, which is expected to offer uniform coverage and high spectral efficiency compared to classical cellular systems. We study in this paper how cell-free massive MIMO can support federated edge learning. Taking advantage of the additive nature of the wireless multiple access channel, over-the-air computation is exploited, where the clients send their local updates simultaneously over the same communication resource. This approach, known as over-the-air federated learning (OTA-FL), is proven to alleviate the communication overhead of federated learning over wireless networks. Considering channel correlation and only imperfect channel state information available at the central server, we propose a practical implementation of OTA-FL over cell-free massive MIMO. The convergence of the proposed implementation is studied analytically and experimentally, confirming the benefits of cell-free massive MIMO for OTA-FL.

翻译：无小区大规模MIMO作为未来无线通信系统的一项有前景技术正崭露头角，相比传统蜂窝系统，它有望提供均匀覆盖和高频谱效率。本文研究无小区大规模MIMO如何支持联邦边缘学习。利用无线多址信道的加性特性，本文采用空中计算技术，使客户端在相同通信资源上同时发送本地更新。该方法称为空中联邦学习（OTA-FL），已被证明可减轻无线网络联邦学习的通信开销。考虑信道相关性及中央服务器仅能获取不完全信道状态信息的实际情况，本文提出一种在无小区大规模MIMO上实现OTA-FL的实用方案。通过理论分析与实验验证，我们确认了无小区大规模MIMO对OTA-FL的提升效果。